{"total":279,"rows":[{"id":"2502.09560","title":"EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents","created":"2025-02-13","cited_by_count":221,"area":"mllm"},{"id":"2503.21460","title":"Large Language Model Agent: A Survey on Methodology, Applications and Challenges","created":"2025-03-27","cited_by_count":205,"area":"agents"},{"id":"2407.06886","title":"Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI","created":"2024-07-09","cited_by_count":179,"area":null},{"id":"2510.03827","title":"LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization","created":"2025-10-04","cited_by_count":179,"area":"vla"},{"id":"2504.19854","title":"NORA: A Small Open-Sourced Generalist Vision Language Action Model for Embodied Tasks","created":"2025-04-28","cited_by_count":127,"area":"lr"},{"id":"2501.16664","title":"Improving Vision-Language-Action Model with Online Reinforcement Learning","created":"2025-01-28","cited_by_count":116,"area":"mllm"},{"id":"2503.23037","title":"Agentic Large Language Models, a survey","created":"2025-03-29","cited_by_count":108,"area":"agents"},{"id":"2505.19789","title":"What Can RL Bring to VLA Generalization? An Empirical Study","created":"2025-05-26","cited_by_count":108,"area":"vla"},{"id":"2507.15597","title":"Being-H0: Vision-Language-Action Pretraining from Large-Scale Human Videos","created":"2025-07-21","cited_by_count":102,"area":"vla"},{"id":"2510.07077","title":"Vision-Language-Action Models for Robotics: A Review Towards Real-World Applications","created":"2025-10-08","cited_by_count":84,"area":"mllm"},{"id":"2505.04769","title":"Vision-Language-Action (VLA) Models: Concepts, Progress, Applications and Challenges","created":"2025-05-07","cited_by_count":74,"area":"mllm"},{"id":"2503.03480","title":"SafeVLA: Towards Safety Alignment of Vision-Language-Action Model via Constrained Learning","created":"2025-03-05","cited_by_count":72,"area":"vla"},{"id":"2506.24044","title":"A Survey on Vision-Language-Action Models for Autonomous Driving","created":"2025-06-30","cited_by_count":72,"area":"mllm"},{"id":"2508.13073","title":"Large VLM-based Vision-Language-Action Models for Robotic Manipulation: A Survey","created":"2025-08-18","cited_by_count":69,"area":"vla"},{"id":"2509.06266","title":"Spatial Reasoning with Vision-Language Models in Ego-Centric Multi-View Scenes","created":"2025-09-08","cited_by_count":63,"area":"lr"},{"id":"2412.11974","title":"Emma-X: An Embodied Multimodal Action Model with Grounded Chain of Thought and Look-ahead Spatial Reasoning","created":"2024-12-16","cited_by_count":47,"area":"lr"},{"id":"2505.16640","title":"BadVLA: Towards Backdoor Attacks on Vision-Language-Action Models via Objective-Decoupled Optimization","created":"2025-05-22","cited_by_count":38,"area":"vla"},{"id":"2501.02765","title":"Visual Large Language Models for Generalized and Specialized Applications","created":"2025-01-06","cited_by_count":36,"area":"mllm"},{"id":"2505.05108","title":"Multi-agent Embodied AI: Advances and Future Directions","created":"2025-05-08","cited_by_count":36,"area":null},{"id":"2408.11537","title":"A Survey of Embodied Learning for Object-Centric Robotic Manipulation","created":"2024-08-21","cited_by_count":35,"area":null},{"id":"2510.24795","title":"A Survey on Efficient Vision-Language-Action Models","created":"2025-10-27","cited_by_count":34,"area":"vla"},{"id":"2512.11891","title":"VLSA: Vision-Language-Action Models with Plug-and-Play Safety Constraint Layer","created":"2025-12-09","cited_by_count":34,"area":"vla"},{"id":"2502.14669","title":"AlphaMaze: Enhancing Large Language Models' Spatial Intelligence via GRPO","created":"2025-02-20","cited_by_count":33,"area":"lr"},{"id":"2512.16760","title":"Vision-Language-Action Models for Autonomous Driving: Past, Present, and Future","created":"2025-12-18","cited_by_count":33,"area":"vla"},{"id":"2507.22424","title":"Spec-VLA: Speculative Decoding for Vision-Language-Action Models with Relaxed Acceptance","created":"2025-07-30","cited_by_count":32,"area":"mllm"},{"id":"2512.22539","title":"VLA-Arena: An Open-Source Framework for Benchmarking Vision-Language-Action Models","created":"2025-12-27","cited_by_count":31,"area":"vla"},{"id":"2504.14650","title":"A Framework for Benchmarking and Aligning Task-Planning Safety in LLM-Based Embodied Agents","created":"2025-04-20","cited_by_count":30,"area":"agents"},{"id":"2602.03310","title":"RDT2: Exploring the Scaling Limit of UMI Data Towards Zero-Shot Cross-Embodiment Generalization","created":"2026-02-03","cited_by_count":30,"area":"vla"},{"id":"2510.06710","title":"RLinf-VLA: A Unified and Efficient Framework for Reinforcement Learning of Vision-Language-Action Models","created":"2025-10-08","cited_by_count":28,"area":"vla"},{"id":"2604.04161","title":"Adaptive Action Chunking at Inference-time for Vision-Language-Action Models","created":"2026-04-05","cited_by_count":28,"area":"vla"},{"id":"2502.03814","title":"Large Language Models for Multi-Robot Systems: A Survey","created":"2025-02-06","cited_by_count":27,"area":null},{"id":"2510.17111","title":"Efficient Vision-Language-Action Models for Embodied Manipulation: A Systematic Survey","created":"2025-10-20","cited_by_count":26,"area":"mllm"},{"id":"2407.08039","title":"Knowledge Overshadowing Causes Amalgamated Hallucination in Large Language Models","created":"2024-07-10","cited_by_count":25,"area":null},{"id":"2509.18953","title":"Eva-VLA: Evaluating Vision-Language-Action Models' Robustness Under Real-World Physical Variations","created":"2025-09-23","cited_by_count":24,"area":"vla"},{"id":"2509.20021","title":"Embodied AI: From LLMs to World Models","created":"2025-09-24","cited_by_count":24,"area":"wm"},{"id":"2411.14982","title":"Large Multi-modal Models Can Interpret Features in Large Multi-modal Models","created":"2024-11-22","cited_by_count":23,"area":"mllm"},{"id":"2603.19199","title":"FASTER: Rethinking Real-Time Flow VLAs","created":"2026-03-19","cited_by_count":21,"area":"vla"},{"id":"2505.19767","title":"RFTF: Reinforcement Fine-tuning for Embodied Agents with Temporal Feedback","created":"2025-05-26","cited_by_count":20,"area":"vla"},{"id":"2410.16400","title":"VipAct: Visual-Perception Enhancement via Specialized VLM Agent Collaboration and Tool-use","created":"2024-10-21","cited_by_count":18,"area":"mllm"},{"id":"2501.03151","title":"Large language models for artificial general intelligence (AGI): A survey of foundational principles and approaches","created":"2025-01-06","cited_by_count":18,"area":"mllm"},{"id":"2511.15669","title":"DeepThinkVLA: Enhancing Reasoning Capability of Vision-Language-Action Models","created":"2025-10-31","cited_by_count":18,"area":"lr"},{"id":"2407.19305","title":"GP-VLS: A general-purpose vision language model for surgery","created":"2024-07-27","cited_by_count":17,"area":"mllm"},{"id":"2506.20966","title":"Parallels Between VLA Model Post-Training and Human Motor Learning: Progress, Challenges, and Trends","created":"2025-06-26","cited_by_count":17,"area":"mllm"},{"id":"2510.09269","title":"Goal-oriented Backdoor Attack against Vision-Language-Action Models via Physical Objects","created":"2025-10-10","cited_by_count":17,"area":"vla"},{"id":"2511.14148","title":"AsyncVLA: Asynchronous Flow Matching for Vision-Language-Action Models","created":"2025-11-18","cited_by_count":17,"area":"vla"},{"id":"2511.16449","title":"Bridging the Semantic-Action Gap in Visual Token Pruning for Efficient VLA Inference","created":"2025-11-20","cited_by_count":17,"area":"vla"},{"id":"2505.01458","title":"A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI","created":"2025-05-01","cited_by_count":16,"area":null},{"id":"2502.10040","title":"Diffusion Trajectory-guided Policy for Long-horizon Robot Manipulation","created":"2025-02-14","cited_by_count":15,"area":"vla"},{"id":"2503.01616","title":"RoboDexVLM: Visual Language Model-Enabled Task Planning and Motion Control for Dexterous Robot Manipulation","created":"2025-03-03","cited_by_count":15,"area":"mllm"},{"id":"2506.23919","title":"Goal-VLA: Image-Generative VLMs as Object-Centric World Models Empowering Zero-shot Robot Manipulation","created":"2025-06-30","cited_by_count":15,"area":"wm"},{"id":"2607.01804","title":"VLA-Corrector: Lightweight Detect-and-Correct Inference for Adaptive Action Horizon","created":"2026-07-02","cited_by_count":15,"area":"vla"},{"id":"2503.01206","title":"Action Tokenizer Matters in In-Context Imitation Learning","created":"2025-03-03","cited_by_count":14,"area":"offlinerl"},{"id":"2502.11518","title":"Generative Multi-Agent Collaboration in Embodied AI: A Systematic Review","created":"2025-02-17","cited_by_count":13,"area":"agents"},{"id":"2503.14504","title":"Aligning Multimodal LLM with Human Preference: A Survey","created":"2025-03-18","cited_by_count":13,"area":"mllm"},{"id":"2506.17629","title":"CLiViS: Unleashing Cognitive Map through Linguistic-Visual Synergy for Embodied Visual Reasoning","created":"2025-06-21","cited_by_count":13,"area":"lr"},{"id":"2505.22050","title":"Reinforced Reasoning for Embodied Planning","created":"2025-05-28","cited_by_count":12,"area":"lr"},{"id":"2602.18532","title":"VLANeXt: Recipes for Building Strong VLA Models","created":"2026-02-20","cited_by_count":12,"area":"mllm"},{"id":"2606.20683","title":"From Question Answering to Task Completion: A Survey on Agent System and Harness Design","created":"2026-06-14","cited_by_count":12,"area":"agents"},{"id":"2602.13191","title":"CoPE-VideoLM: Leveraging Codec Primitives For Efficient Video Language Modeling","created":"2026-02-13","cited_by_count":11,"area":null},{"id":"2604.13942","title":"Goal2Skill: Long-Horizon Manipulation with Adaptive Planning and Reflection","created":"2026-04-15","cited_by_count":11,"area":"vla"},{"id":"2606.10267","title":"What Matters in Orchestrating Robot Policies: A Systematic Study of Hierarchical VLA Agents","created":"2026-06-09","cited_by_count":11,"area":"vla"},{"id":"2505.07634","title":"Neural Brain: A Neuroscience-inspired Framework for Embodied Agents","created":"2025-05-12","cited_by_count":10,"area":"agents"},{"id":"2510.12693","title":"ERA: Transforming VLMs into Embodied Agents via Embodied Prior Learning and Online Reinforcement Learning","created":"2025-10-14","cited_by_count":10,"area":"mllm"},{"id":"2603.27670","title":"ProgressVLA: Progress-Guided Diffusion Policy for Vision-Language Robotic Manipulation","created":"2026-03-29","cited_by_count":10,"area":"vla"},{"id":"2606.23686","title":"LIBERO-Safety: A Comprehensive Benchmark for Physical and Semantic Safety in Vision-Language-Action Models","created":"2026-06-22","cited_by_count":10,"area":"vla"},{"id":"2410.05026","title":"Active Fine-Tuning of Multi-Task Policies","created":"2024-10-07","cited_by_count":9,"area":"offlinerl"},{"id":"2410.05191","title":"LADEV: A Language-Driven Testing and Evaluation Platform for Vision-Language-Action Models in Robotic Manipulation","created":"2024-10-07","cited_by_count":9,"area":"mllm"},{"id":"2503.16965","title":"Praxis-VLM: Vision-Grounded Decision Making via Text-Driven Reinforcement Learning","created":"2025-03-21","cited_by_count":9,"area":"lr"},{"id":"2504.16939","title":"A Desideratum for Conversational Agents: Capabilities, Challenges, and Future Directions","created":"2025-04-07","cited_by_count":9,"area":"agents"},{"id":"2510.01068","title":"Compose Your Policies! Improving Diffusion-based or Flow-based Robot Policies via Test-time Distribution-level Composition","created":"2025-10-01","cited_by_count":9,"area":"vla"},{"id":"2511.06754","title":"SlotVLA: Towards Modeling of Object-Relation Representations in Robotic Manipulation","created":"2025-11-10","cited_by_count":9,"area":null},{"id":"2602.01745","title":"Probability-Entropy Calibration: An Elastic Indicator for Adaptive Fine-tuning","created":"2026-02-02","cited_by_count":9,"area":null},{"id":"2603.01581","title":"KERV: Kinematic-Rectified Speculative Decoding for Embodied VLA Models","created":"2026-03-02","cited_by_count":9,"area":"vla"},{"id":"2407.03967","title":"Investigating the Role of Instruction Variety and Task Difficulty in Robotic Manipulation Tasks","created":"2024-07-04","cited_by_count":8,"area":null},{"id":"2503.24070","title":"HACTS: a Human-As-Copilot Teleoperation System for Robot Learning","created":"2025-03-31","cited_by_count":8,"area":null},{"id":"2508.04681","title":"Perceiving and Acting in First-Person: A Dataset and Benchmark for Egocentric Human-Object-Human Interactions","created":"2025-08-06","cited_by_count":8,"area":null},{"id":"2510.23763","title":"RoboOmni: Proactive Robot Manipulation in Omni-modal Context","created":"2025-10-27","cited_by_count":8,"area":"mllm"},{"id":"2602.21445","title":"VLA Knows Its Limits: Adaptive Execution Horizons for Robot Policies","created":"2026-02-24","cited_by_count":8,"area":"vla"},{"id":"2604.23001","title":"Vision-Language-Action in Robotics: A Survey of Datasets, Benchmarks, and Data Engines","created":"2026-04-24","cited_by_count":8,"area":"vla"},{"id":"2605.13403","title":"RotVLA: Rotational Latent Action for Vision-Language-Action Model","created":"2026-05-13","cited_by_count":8,"area":"vla"},{"id":"2505.08854","title":"Generative AI for Autonomous Driving: Frontiers and Opportunities","created":"2025-05-13","cited_by_count":7,"area":"driving"},{"id":"2505.12343","title":"Mitigating Hallucinations via Inter-Layer Consistency Aggregation in Large Vision-Language Models","created":"2025-05-18","cited_by_count":7,"area":"mllm"},{"id":"2508.15201","title":"Survey of Vision-Language-Action Models for Embodied Manipulation","created":"2025-08-21","cited_by_count":7,"area":"vla"},{"id":"2509.18597","title":"Growing with Your Embodied Agent: A Human-in-the-Loop Lifelong Code Generation Framework for Long-Horizon Manipulation Skills","created":"2025-09-23","cited_by_count":7,"area":"agents"},{"id":"2509.24997","title":"PanoWorld-X: Generating Explorable Panoramic Worlds via Sphere-Aware Video Diffusion","created":"2025-09-29","cited_by_count":7,"area":"diffusion"},{"id":"2510.04898","title":"HyperVLA: Efficient Inference in Vision-Language-Action Models via Hypernetworks","created":"2025-10-06","cited_by_count":7,"area":"vla"},{"id":"2512.09927","title":"Token Expand-Merge: Training-Free Token Compression for Vision-Language-Action Models","created":"2025-12-10","cited_by_count":7,"area":"vla"},{"id":"2602.00500","title":"Inject Once Survive Later: Backdooring Vision-Language-Action Models to Persist Through Downstream Fine-tuning","created":"2026-01-31","cited_by_count":7,"area":"vla"},{"id":"2602.05765","title":"RL-VLA$^3$: A Flexible and Asynchronous Reinforcement Learning Framework for VLA Training","created":"2026-02-05","cited_by_count":7,"area":"vla"},{"id":"2602.11291","title":"H-WM: Robotic Task and Motion Planning Guided by Hierarchical World Model","created":"2026-02-11","cited_by_count":7,"area":"wm"},{"id":"2505.05540","title":"Benchmarking Vision, Language, & Action Models in Procedurally Generated, Open Ended Action Environments","created":"2025-05-08","cited_by_count":6,"area":"vla"},{"id":"2510.16263","title":"NEBULA: Do We Evaluate Vision-Language-Action Agents Correctly?","created":"2025-10-17","cited_by_count":6,"area":"vla"},{"id":"2602.16931","title":"Narrow Fine-Tuning Erodes Safety Alignment in Vision-Language Agents","created":"2026-02-18","cited_by_count":6,"area":"mllm"},{"id":"2603.14523","title":"VLA-Thinker: Boosting Vision-Language-Action Models through Thinking-with-Image Reasoning","created":"2026-03-15","cited_by_count":6,"area":"lr"},{"id":"2603.17573","title":"HeiSD: Hybrid Speculative Decoding for Embodied Vision-Language-Action Models with Kinematic Awareness","created":"2026-03-18","cited_by_count":6,"area":"vla"},{"id":"2603.28565","title":"StreamingVLA: Streaming Vision-Language-Action Model with Action Flow Matching and Adaptive Early Observation","created":"2026-03-30","cited_by_count":6,"area":"vla"},{"id":"2604.23121","title":"Breaking Lock-In: Preserving Steerability under Low-Data VLA Post-Training","created":"2026-04-25","cited_by_count":6,"area":"vla"},{"id":"2605.26820","title":"Can Vision-Language-Action Models Learn from Real-World Data Continually without Forgetting?","created":"2026-05-26","cited_by_count":6,"area":"vla"},{"id":"2605.27920","title":"Rethinking Video-Language Model from the Language Input Perspective","created":"2026-05-27","cited_by_count":6,"area":"lr"},{"id":"2606.11324","title":"Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models","created":"2026-06-09","cited_by_count":6,"area":"lr"}],"next_cursor":"100"}